Predicting the current and future distribution of the western black-legged tick, Ixodes pacificus, across the Western US using citizen science collections

Abstract

In the twenty-first century, ticks and tick-borne diseases have expanded their ranges and impact across the US. With this spread, it has become vital to monitor vector and disease distributions, as these shifts have public health implications. Typically, tick-borne disease surveillance (e.g., Lyme disease) is passive and relies on case reports, while disease risk is calculated using active surveillance, where researchers collect ticks from the environment. Case reports provide the basis for estimating the number of cases; however, they provide minimal information on vector population or pathogen dynamics. Active surveillance monitors ticks and sylvatic pathogens at local scales, but it is resource-intensive. As a result, data are often sparse and aggregated across time and space to increase statistical power to model or identify range changes. Engaging public participation in surveillance efforts allows spatially and temporally diverse samples to be collected with minimal effort. These citizen-driven tick collections have the potential to provide a powerful tool for tracking vector and pathogen changes. We used MaxEnt species distribution models to predict the current and future distribution of Ixodes pacificus across the Western US through the use of a nationwide citizen science tick collection program. Here, we present niche models produced through citizen science tick collections over two years. Despite obvious limitations with citizen science collections, the models are consistent with previously-predicted species ranges in California that utilized more than thirty years of traditional surveillance data. Additionally, citizen science allows for an expanded understanding of I. pacificus distribution in Oregon and Washington. With the potential for rapid environmental changes instigated by a burgeoning human population and rapid climate change, the development of tools, concepts, and methodologies that provide rapid, current, and accurate assessment of important ecological qualities will be invaluable for monitoring and predicting disease across time and space.

Citizen Science Provides an Efficient Method for Broad-Scale Tick-Borne Pathogen Surveillance of Ixodes pacificus and Ixodes scapularis across the United States

“…Citizen science collections can also create finer spatial uncertainties as well (i.e., state-state and county-county aberrations) that are harder to detect and quantify within the data set. Such spatial discordance can be easily attributed to county-to-county travel; however, they could also be evidence of tick/pathogen range expansions, especially when several submissions across time are received from a single county ( 20 ). In the future, we would advocate for a streamlined method to easily and accurately collect travel data associated with each submission to help limit these challenges.…”

“…In the future, we would advocate for a streamlined method to easily and accurately collect travel data associated with each submission to help limit these challenges. Even with these challenges, citizen science-based collections can characterize vector and pathogen distributions across large portions of the United States that compare favorably with active surveillance efforts ( 18 , 20 , 21 ) and broadly reflect clinical cases ( 22 ).…”

“…These benefits are leveraged by harnessing citizen scientists’ interest in collecting and submitting ticks they encounter, therefore providing a method to supplement traditional surveillance methods that might be conducted at restricted temporal or spatial extents. The accuracy and validity of citizen science data are limited by their nature (e.g., lack of sampling control and verification), and in some cases, these limitations mirror those found in human disease reporting or field collections: namely, the unknown certainty of exposure sites and a lack of spatial and temporal uniformity in surveillance effort ( 8 , 10 , 18 , 20 ). Despite these possible drawbacks, this approach can undoubtedly augment traditional surveillance techniques and provide valuable insights into TBD ecology and epidemiology.…”

“…Despite these possible drawbacks, this approach can undoubtedly augment traditional surveillance techniques and provide valuable insights into TBD ecology and epidemiology. Additionally, citizen science collections can efficiently monitor traditionally nonendemic areas for pathogen emergence as these areas are rarely monitored through traditional active surveillance campaigns ( 20 ).…”

Predicting the Potential Global Distribution of Amblyomma americanum (Acari: Ixodidae) under Near Current and Future Climatic Conditions, Using the Maximum Entropy Model

“…The models in some similar studies used the species occurrence data with data on the climatic variables and some species characteristics to find the current geographic distribution area and future areas under various climatic scenarios [24,25]. The maximum entropy model is one of the models used to predict current and future potential areas of geographic distribution [26], especially for invasion biology [27], protection of biodiversity [28] and the transmission risks of parasitic diseases [29].…”